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禪定腦電波之非線性動態回歸現象的頻率空間特性研究=Spatio-spectral characterization of nonlinear dynamical recurrence of Zen-meditation EEG |
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温智竣 (著)=Wen, Chih-chun (au.)
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| Date | 2020 |
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| Pages | 115 |
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| Publisher | 國立交通大學 |
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| Publisher Url |
https://www.nycu.edu.tw/
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| Location | 新竹市, 臺灣 [Hsinchu shih, Taiwan] |
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| Content type | 博碩士論文=Thesis and Dissertation |
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| Language | 英文=English |
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| Degree | master |
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| Institution | 國立交通大學 |
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| Department | 電控工程研究所 |
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| Advisor | 羅佩禎 |
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| Publication year | 109 |
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| Keyword | 腦電波=Electroencephalograph; 腦圖=brain mapping; 頻率空間特性=spatio-spectral property; 連續小波轉換=continuous wavelet transform; 自主織映射網路 =Self-organizing map; 非線性動態特性理論=nonlinear dynamical theory; 回歸圖=recurrence plot; 禪定=Zen meditation |
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| Abstract | This study investigates the Zen-meditation brain dynamics by recurrence analysis and correlates the nonlinear dynamical properties with the spatio-spectral properties of 30-channel Zen-meditation EEG (electroencephalograph). First of all, continuous wavelet transform (CWT) is implemented to decompose EEG into six rhythmic bands. The final dataset is composed of brain potential mappings at the peaks of Cz in each rhythmic band. To classify the behavior of spatio-spectral properties, the unsupervised learning method, self-organizing map (SOM) is employed. The second part of this thesis is the characterization of nonlinear brain dynamics based on embedding theories and reconstructed EEG phase trajectory. To analyze the phase trajectory of nonlinear system characterizing the brain dynamics, we construct the recurrence plot from a 5-second segment of each EEG channel The recurrence plot is further quantified by recurrent parameters to observe the behavior of recurrence of particular system states. SOM clustering result of the brain potential mapping at Cz peaks (BPP) in each EEG rhythmic band will be correlated with the brain mapping of recurrence (BMR) to observe the spatio-spectral characteristics of nonlinear dynamical recurrence.
本論文透過回歸和30通道禪定腦電波頻率時空特性研究禪定腦電波的動態特性。首先，使用連續小波變換（CWT）將EEG分解為六個頻段。最終數據集由每個頻段的通道Cz峰值的腦電勢圖組成。為了對頻率空間特性的行為進行分類，採用了非監督學習方法，即自組織映射網路（SOM）。本文的第二部分使用嵌入理論和重構腦電相位軌跡描述非線性腦動態特性。為了分析腦的動態非線性系統的相位軌跡，我們從每個通道5秒EEG構建了一個回歸圖，該圖由回歸參數進一步量化，以觀察特定系統狀態的回歸行為。分析每個六頻段腦電圖中通道Cz峰值（BPP）處的腦電勢圖的SOM群聚結果將與回歸（BMR）的腦圖關聯性，以觀察非線性動態回歸的頻率空間特徵。 |
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| Table of contents | 摘要 i
Abstract ii
誌謝 iv
Content v
List of abbreviation vii
List of Figures viii
List of tables xi
Chapter 1 Introduction 1
1-1 Background and Motivation 1
1-2 Scope of this Thesis 4
Chapter 2 Theories and Methods 5
2-1 Continuous Wavelet Transform (CWT) 5
2-1-1 Continuous wavelet transform 5
2-1-2 Six EEG rhythmic bands 8
2-2 Self-Organizing Map (SOM) 10
2-3 Nonlinear Recurrence Analysis 18
2-3-1 Construction of recurrence plot 18
2-3-2 Quantification of the recurrence plot 19
2-3-3 Brain mappings of recurrence parameters (BMR) 23
2-4 Evaluation SOM clustering performance 23
2-4-1 Cluster center 23
2-4-2 Fault cluster rate (FCR) 24
Chapter 3 Strategy and Implementation 25
3-1 Outline of Complete Scheme 25
3-2 Classification of Brain Mappings of Six EEG Rhythmic Bands 27
3-2-1 Brain Mapping Construction 27
3-2-2 SOM implementation 29
3-2-3 SOM parameter analysis 31
3-3 Issues of Recurrence Plot Analysis 40
3-3-1 Parameters for constructing recurrence plot 40
3-3-2 Effect of window size on estimate of recurrent parameters 43
Chapter 4 Results 62
4-1 Correlation between Clustering Results and Recurrent Parameters 63
4-1-1 Outline of complete scheme for section 4-1 64
4-1-2 Major cluster for different EEG rhythmic bands 65
4-1-3 Results of brain mapping of recurrence (BMR) 68
4-2 Extremal Recurrence Rate (%γ) Correlating with Clustering of Six EEG Rhythmic Bands 91
4-2-1 Outline of complete scheme for section 4-2 91
4-2-2 Extremal recurrence rate (%????) correlating with BPP clustered by SOM. 93
Chapter 5 Conclusions and Future work 102
5-1 Conclusions 102
5-2 Future work 103
Appendix A Orthodox Zen Meditation 104
Appendix B Raw EEG for Figure 4-13 106
Reference 109 |
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| Hits | 363 |
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| Created date | 2022.10.14 |
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| Modified date | 2023.02.17 |
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